Center of Excellence for Mobile Sensor Data-to-Knowledge (MD2K) - OVERALL

移动传感器数据到知识 (MD2K) 卓越中心 - 总体

基本信息

批准号：
9087238
负责人：
Santosh Kumar
金额：
$ 264.54万
依托单位：
UNIVERSITY OF MEMPHIS
依托单位国家：
美国
项目类别：
财政年份：
2014
资助国家：
美国
起止时间：
2014-09-29 至 2018-09-30
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/9087238
关键词：
Address Algorithms Architecture Area Asthma Back Behavior Behavioral Big Data Biological Biomedical Research Cardiovascular Diseases Chronic Disease Clinical Communities Complex Computer software Computing Methodologies Congestive Heart Failure Data Data Analyses Data Analytics Data Science Devices Diabetes Mellitus Disease Documentation E-learning Educational Curriculum Environment Environmental Risk Factor Etiology Event Foundations Funding Genetic Genomics Goals Health Healthcare Image Imagery Individual Intervention Investments Knowledge Knowledge Discovery Malignant Neoplasms Measures Medicine Mental Depression Methods Mining Obesity Participant Patient Care Patient Monitoring Patient Self-Report Patients Pattern Persons Population Prevention strategy Preventive Process Provider Relapse Research Personnel Research Training Risk Factors Science Semantics Series Smoker Software Tools Staging Standardization Structure System Technology Time Training United States United States National Institutes of Health Vision base big biomedical data burden of illness care delivery computer infrastructure data to knowledge design disorder risk experience handheld mobile device improved instructor mHealth open source prevent public health relevance sensor social software development theories tool treatment response usability

Address Algorithms Architecture Area Asthma Back Behavior Behavioral Big Data Biological Biomedical Research Cardiovascular Diseases Chronic Disease Clinical Communities Complex Computer software Computing Methodologies Congestive Heart Failure Data Data Analyses Data Analytics Data Science Devices Diabetes Mellitus Disease Documentation E-learning Educational Curriculum Environment Environmental Risk Factor Etiology Event Foundations Funding Genetic Genomics Goals Health Healthcare Image Imagery Individual Intervention Investments Knowledge Knowledge Discovery Malignant Neoplasms Measures Medicine Mental Depression Methods Mining Obesity Participant Patient Care Patient Monitoring Patient Self-Report Patients Pattern Persons Population Prevention strategy Preventive Process Provider Relapse Research Personnel Research Training Risk Factors Science Semantics Series Smoker Software Tools Staging Standardization Structure System Technology Time Training United States United States National Institutes of Health Vision base big biomedical data burden of illness care delivery computer infrastructure data to knowledge design disorder risk experience handheld mobile device improved instructor mHealth open source prevent public health relevance sensor social software development theories tool treatment response usability

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项目摘要

DESCRIPTION (provided by applicant): Rapid advances in technology, are leading to field-deployable mobile sensing devices that can now be used to quantify complex dynamics across time of key physical, biological, behavioral, social, and environmental factors that contribute to health and disease risk. These data will enable us to break through to the next level of biomedical understanding of causation in complex disorders. While ongoing efforts have made significant strides in the analysis of "big data" in the areas of genomics, imaging, and EHR, significant new investment is needed to develop and disseminate data analytics tools specific to the unique features of mobile sensor data (e.g., high volume, velocity, variety, variability, and versatility) to convert this wealth of data into information, knowledge, and action. Investment in strong, open, scientific, and computational infrastructure for mobile "big data" at this early stag promises outsize returns to advance science and improve health. The Center of Excellence for Mobile Sensor Data-to-Knowledge (MD2K) will generate generalizable theory, methods, tools, and software, to address major barriers to processing complex mobile sensor data and its use in biomedical knowledge discovery and just-in-time care delivery, laying the foundation for P5 Medicine. It will develop and implement a standards-based, interoperable, extensible and open-source big data software platform for efficient implementation of MD2K data analytics. The MD2K Center will demonstrate the feasibility, utility, and generalizability of the MD2K approach by implementing the entire MD2K data analytics system in the context of two biomedical applications - reducing relapse among abstinent daily smokers and reducing readmission among congestive heart failure (CHF) patients. All the tools and software developed by the Center will be freely available as standards-compliant and open-source with documentation to engage data science researchers in advancing the science of MD2K and its integration with other biomedical big data such as EHRs, genomics, and imaging. The Center will provide training materials to help biomedical researchers install the MD2K software on their mobile devices and servers to collect mobile sensor data and analyze these data for biomedical discovery.

描述（由申请人提供）：技术的快速进步，正在导致可采用的移动传感设备，这些设备现在可以用于跨关键的物理，生物学，行为，社交和环境因素的关键时间量化复杂的动态，这些动态有助于健康和疾病风险。这些数据将使我们能够突破对复杂疾病因果关系的新生物医学理解。尽管正在进行的努力在分析基因组学，成像和EHR领域的“大数据”方面取得了长足的进步，但需要进行大量新投资，以开发和传播针对移动传感器数据独特功能（例如，大量，速度，速度，品种，变异性和多功能性）的独特功能，以将数据的财富转化为信息，知识，知识，知识，知识，知识，知识和行动。在此早期的雄鹿中，对移动“大数据”的强大，开放，科学和计算基础架构的投资有望超出科学的回报并改善健康。移动传感器数据对知识的卓越中心（MD2K）将生成可概括的理论，方法，工具和软件，以解决处理复杂的移动传感器数据及其在生物医学知识发现和即时护理中的使用的主要障碍，并为P5药物奠定了基础。它将开发和实施基于标准的，可互操作，可扩展和开源的大数据软件平台，以有效地实现MD2K数据分析。 MD2K中心将通过在两种生物医学应用的背景下实施整个MD2K数据分析系统，证明MD2K方法的可行性，实用性和概括性 - 减少日常吸烟者的复发并减少充血性心力衰竭（CHF）患者的复发。该中心开发的所有工具和软件将作为符合标准和开源的文档免费提供，以吸引数据科学研究人员推进MD2K的科学及其与其他生物医学大数据（例如EHR，基因组学和成像）的集成。该中心将提供培训材料，以帮助生物医学研究人员在其移动设备和服务器上安装MD2K软件，以收集移动传感器数据并分析这些数据以进行生物医学发现。